9944 results for "cancer rna-seq"

in 56.21 milliseconds.

• TransNEO neoadjuvant breast cancer study

  Study EGAS00001004582

• Transcriptomic characterization of the histopathological growth patterns in breast cancer liver metastases

  Characterizing transcriptommic profiles of the two main histopathological growth patterns in liver metastases in patients with breast cancer.

  Study EGAS50000000225

• Coding and small non-coding transcriptional landscape of tuberous sclerosis complex cortical tubers: implications for pathophysiology and treatment

  Tuberous Sclerosis Complex (TSC) is a rare genetic disorder that results from a mutation in the TSC1 or TSC2 genes leading to constitutive activation of the mechanistic target of rapamycin complex 1 (mTORC1). TSC is associated with autism, intellectual disability and severe epilepsy. Cortical tubers are believed to represent the neuropathological substrates of these disabling manifestations in TSC. In the presented study we used high-throughput RNA sequencing in combination with systems-based computational approaches to investigate the complexity of the TSC molecular network. Overall we detected 438 differentially expressed genes and 991 differentially expressed small non-coding RNAs in cortical tubers compared to autopsy control brain tissue. We observed increased expression of genes associated with inflammatory, innate and adaptive immune responses. In contrast, we observed a down-regulation of genes associated with neurogenesis and glutamate receptor signaling. MicroRNAs represented the largest class of over-expressed small non-coding RNA species in tubers. In particular, our analysis revealed that the miR-34 family (including miR-34a, miR-34b and miR-34c) was significantly over-expressed. Functional studies demonstrated the ability of miR-34b to modulate neurite outgrowth in mouse primary hippocampal neuronal cultures. This study provides new insights into the TSC transcriptomic network along with the identification of potential new treatment targets.

  Study EGAS00001002485

• Viral Respiratory Pathogens Genetics

  The overall purpose of this study is to investigate the host genetic factors in response to influenza virus infection, with the focus on influenza vaccination in the first substudy "Adult Influenza Vaccine Genetics" and with the focus on influenza natural infection and other acute respiratory infections (ARIs) in the second substudy "Acute Viral Respiratory Infection Genetics". In the first substudy, healthy adults were enrolled in 2008 (male cohort) and 2010 (female cohort) and immunized with seasonal influenza vaccine. In the second substudy, healthy adults were invited to enroll to be followed for acute respiratory illness through two consecutive influenza seasons 2009-2010 and 2010-2011. Peripheral blood genomic DNA samples were collected from all the subjects, and time-series RNA and serum samples were obtained pre- and post- immunization/infection. Genotyping was carried out on peripheral blood genomic DNA samples using Illumina HumanOmniExpress-12 v1 arrays. Peripheral blood RNA samples obtained at each visit were analyzed using Illumina Human HT-12 (for all the samples) and HiSeq 2000 (for 130 samples in the "Acute Viral Respiratory Infection Genetics" study). Serum specimens were tested using hemagglutination-inhibition (HAI) antibody assay for Influenza H1N1, H3N2, and Influenza B strains. A detailed description of each substudy is provided under their own pages below and via the grouping tool in the right-hand box: phs000635 Adult Influenza Vaccine Genetics phs001031 Acute Viral Respiratory Infection Genetics

  Study phs001030

• Phase 2 Study of Nivolumab and Entinostat in Unresectable or Metastatic Cholangiocarcinoma and Pancreatic Adenocarcinoma

  The study was a single-center, open-label, phase II trial (registration no. NCT03250273) designed to evaluate the efficacy of entinostat in combination with nivolumab in patients with advanced pancreatic ductal adenocarcinoma (PDAC). The aim was to assess the objective response rate using RECIST v1.1 criteria as the primary endpoint. A total of 27 patients with advanced PDA were enrolled from November 2017 to November 2020. Their treatment involved a 14-day lead-in with entinostat monotherapy, followed by a combination with nivolumab. The study utilized several molecular technologies to assess immune profiles and tumor microenvironment (TME) changes: high-dimensional mass cytometry by time of flight (CyTOF), Luminex for chemokine analysis in plasma, multiplexed immunohistochemistry (mIHC), image cytometry-based quantification, bulk RNA sequencing analysis. The objective response rate (ORR) was 11% with three patients showing a partial response (PR). The median duration of response was 10.2 months. Grade ≥ 3 treatment-related adverse events (TRAEs) occurred in 63% of patients, with the most common being decreased lymphocyte count, anemia, hypoalbuminemia, and hyponatremia. Gene expression analysis showed an enrichment in inflammatory response signaling pathways with the combination treatment. RNA sequencing data with clinical and demographic patient information will be available through dbGaP. For expression summaries, please refer to GEO submission GSE248014.

  Study phs003615

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Colorectal_LCM (2020-02-20)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005994

• De Novo Characterization of Cell-Free DNA Fragmentation Hotspots in Plasma Whole-Genome Sequencing

  The raw sequencing data deposited here are low-coverage (~1X) whole-genome sequencing (WGS) of plasma cell-free DNA (cfDNA). The purpose is to validate the performance of early-stage cancer diagnosis in the Zhou et al. 2020 BioRxiv paper, mainly for two types of cancer: early-stage liver cancer and breast cancer. The cases and controls are matched with age, gender, smoking history, and alcohol usage. We developed a computational method to identify the cfDNA fragmentation hotspots from pooled low-coverage cfDNA WGS data. We found the cfDNA fragmentation hotspots are highly enriched in regulatory regions, such as open chromatin regions. The signals from these regions can help the diagnosis of early-stage cancers and their tissues-of-origin.

  Study phs003062

• Foundation Medicine Adult Cancer Clinical Dataset (FM-AD)

  The Foundation Medicine adult cancer clinical dataset consists of 18,004 unique solid tumor samples that underwent genomic profiling on a single uniform platform as part of standard clinical care. The dataset is derived from the FoundationOne® genomic profiling assay version 2 that interrogates exonic regions of 287 cancer-related genes and selected introns from 19 genes known to undergo rearrangements in human cancer. Genomic DNA samples were sequenced to over 500x median coverage, and custom computational analyses identified all classes of genomic alterations (base substitutions, insertions and deletions, copy number alterations, and rearrangements). Since matched normal tissue was unavailable for analysis, these data underwent additional filtering to enrich for cancer-related events. The reported data includes genomic alterations that are known and suspected tumor drivers, as well as variants of unknown significance. To preserve patient anonymity, all known or suspected germline variants were removed from the data unless known to be associated with cancer development. The dataset contains genomic alteration profiles generated by FoundationOne version 2 testing for adult cancer patients (over 18 y.o.), and represents a vast diversity of tumor subtypes, including many rare diseases not profiled as part of large-scale profiling efforts. Cases are grouped into 16 broad disease categories containing tumors from 162 unique disease subtypes. Since specimens were profiled as part of clinical care, limited clinical parameters were available, including age, gender, tissue of origin, % of tumor nuclei, and diagnosis. Publication of this dataset is intended to allow the broad scientific community access to this unique cohort for use in scientific research projects of common and rare types of cancer, both for generating leads regarding causal mechanisms as well as cross-testing and confirming existing hypotheses. A pediatric cancer clinical dataset consisting of data from 1,215 patients under 18 y.o. is available separately at: FOUNDATION MEDICINE

  Study phs001179

• Childhood Cancer Data Initiative (CCDI): Enhancement of Data Sharing in Pediatric, Adolescent and Young Adult Cancers

  NCI's Childhood Cancer Data Initiative (CCDI) is building a community centered around childhood cancer care and research data. Through enhanced data sharing, we can improve our understanding of cancer biology to improve preventive measures, treatment, quality of life, and survivorship, as well as ensure that researchers learn from every child with cancer. While childhood cancers represent the leading cause of death in children over the age of 1, they are collectively rare, comprising approximately 1%‒3% of cancers diagnosed annually in the United States. Information on diagnosis, treatment, and outcomes is often stored at the hospital or institution where a child is treated, making it difficult to answer scientific questions about childhood cancer. Sharing clinical care and research data generated by children's hospitals, clinics, or networks broadly with the community can help us learn faster and, on a scale much larger than any single institution caring for children can learn on its own. To exploit the rapid advances in high-throughput DNA sequencing technologies and realize the goals of precision cancer medicine, the UMICH Cancer Center established the Michigan Oncology Sequencing Center (MI-ONCOSEQ). This UMICH Cancer Center provisions genomic data derived from the Michigan Oncology Sequencing Center (MI-ONCOSEQ) clinical sequencing assay for patients that fall within the inclusion criteria of the CCDI data sharing initiative. An "integrative sequencing approach" carried out in a CLIA-certified laboratory is utilized to provide a comprehensive landscape of the genetic alterations in individual tumor specimens for the purpose of identifying informative and/or actionable mutations. Using a number of computational pipelines that we have developed in-house or have adapted from the public domain, candidate molecular aberrations are nominated and then analyzed by scientists for clinical significance and/or relevance. This approach enables the detection of point mutations, insertions/deletions, gene fusions and rearrangements, amplifications/deletions, and outlier expressed genes. Furthermore, we can identify certain germline alterations that may also be relevant.

  Study phs002431

• The whole blood of female volunteers and sperm from the male volunteer were used to extract genomic DNA to do whole genome sequencing. Distinguished SNPs between parental genomes were retained to analyze parental allele-specific DNA methylation and chromatin accessibility in scCOOL-seq data.

  DNA methylation, chromatin states, and their interrelationships represent critical epigenetic information, but those are largely unknown in human early embryos. Here, we apply scCOOL-seq (Chromatin Overall Omic-scale Landscape Sequencing) to generate a genome-wide map of DNA methylation and chromatin accessibility at single-cell resolution during human preimplantation development. Unlike in mice, the chromatin of paternal genome is already more open than that of maternal genome at the mid-zygote stage in humans, and this state is maintained until the 4-cell stage. After fertilization, genes with high variations in DNA methylation and those with high variations in chromatin accessibility tend to be two different sets. Furthermore, 1,797 (35%) out of 5,155 widely open chromatin regions in promoters closed when transcription activity was inhibited, indicating a feedback mechanism between transcription and open chromatin maintenance. Our work paves the way for dissecting the complex, yet highly coordinated, epigenetic reprogramming during human preimplantation development.

  Study EGAS00001002987

• ScRNA-seq of human kidney immune cells of patients with ANCA-associated glomerulonephritis, Lupus Nephritis against a "healthy" nephrectomy control

  ANCA-associated glomerulonephritis (AGN) associates with a high risk of end-stage kidney disease. The role of kidney immune cells in local inflammation remains unclear. Here, we investigate kidney immune cell diversity and function. Kidney tissue from AGN patients (n=5) and a lupus nephritis (LN) patient (n=1) were aquired during a biopsy procedure for a clinical indication. Needle-core biopsies were obtained for histopathological examination, and an additional pass was performed to retrieve kidney tissue for scRNA-seq. Healthy kidney tissue (n=1) was obtained from a kidney that was surgically removed do tue due to a (non-invasive) papillary urothelial carcinoma. Immediately after collection, kidney tissue was processed into a single-cell suspension and sorted using a 4-color flow cytometry panel to isolate living, CD45+ immune cells. To aid in the multi-omic characterization, surface markers and T and B cell repertoires were sequenced in 2 samples (1 AGN patient and the nephrectomy control). These samples were incubated with an oligo-antibody TotalSeq-C cocktail containing 130 unique cell surface antigens.

  Study EGAS50000000159

• The Genomic Landscape of Prostate Cancer Brain Metastases

  Study EGAS00001004557

• Cancer Research UK manchester Institute Cancer Biomarker Centre

  Dac EGAC00001001765

• KCL PRECSION Mutations targeted-seq

  105 Normal, DCIS and recurrences samples target-sequenced

  Dataset EGAD00001008376

• Mixture of 4

  Mixture of 4 unrelated individuals sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008724

• Mixture of 3

  Mixture of 3 unrelated individuals sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008729

• 17 skin and oral epithelial bulk samples from 2 donors

  Aligned BAM files with removed duplicate reads of targeted sequencing data (exomes of a panel of 153 genes) from 12 skin and 5 oral epithelial bulk samples from 2 donors. Sequences generated by the BGI DNB-SEQ platform.

  Dataset EGAD00001008956

• Single cell epigenomic study of H3-K27M mutant diffuse midline glioma across age and location

  This dataset contains the open chromatin profiles of 8 patient H3-K27M mutant DMGs utilizing the single-cell/nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq)

  Dataset EGAD00001010170

• Chromatin accessibility in human monocytes differentiation

  This dataset consists of ATAC-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. In total, it includes 39 samples.

  Dataset EGAD00001007953

• Transcriptome atlas of brain organoid developent

  Single-cell Cut&Tag of three histone modifications and chromatin accessibility over a timecourse of brain organoid development from pluripotency. We profiled 5 time points of brain organoid development and 2 time points of retinal organoid development. We used scRNA-seq to profile transcriptome. Library preparation was carried out with the 10x genomics platform.

  Dataset EGAD50000000223

• BIOMIROX

  This dataset regroups RNAseq of paired primary colorectal cancers and liver metastases extracted from 113 patients In Paris and Besançon University Hospitals. 216 FASTQ files from single-end 3' PolyA (QuantSeq 3′mRNA-Seq Kit FWD for Illumina (Lexogen)) RNAseq samples were generated On NOVASEQ 6000 (ILLUMINA).

  Dataset EGAD50000000443

• WTCCC case-control study for Breast cancer

  WTCCC genome-wide case-control association study for Breast cancer (BC) using the 1958 British Birth Cohort collection as controls.

  Study EGAS00000000024

• Somatic_mutations_in_twin_breast_cancers

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history.

  Study EGAS00001002379

• OCCAMS_Oesophageal Cancer Organoids_1

  ***THIS DATA CAN ONLY BE USED FOR NON-COMMERCIAL CANCER RESEARCH*** Sequencing of organoid cell lines derived from oesophageal tumour sections taken from patients diagnosed with primary oesophageal cancer who underwent tumour resection surgery.

  Dataset EGAD00001001889

• Framome cancer samples

  Cancer samples for neo-open reading frame peptides that comprise the tumor framome are a rich source of neoantigens for cancer immunotherapy.

  Dataset EGAD50000000420

• National Cancer Institute (NCI) Prostate Cancer Genome-Wide Association Study for Uncommon Susceptibility Loci (PEGASUS)

  This genome-wide association study was funded by the National Cancer Institute (NCI) to identify uncommon susceptibility loci for prostate cancer. A total of 4,600 prostate cancer cases and 2,840 controls of European ancestry from the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were genotyped using the Illumina HumanOmni2.5 and passed rigorous quality control filters. Additional genotype data (available in dbGap under other accession numbers) from 101 independent controls of European ancestry scanned with the HumanOmni2.5 were also included, resulting in a total of 4,600 cases and 2,941 controls for the published analysis. SNPs from the most promising regions, as determined by rank p-value, under multiple different models as well as select candidate genes were taken forward for replication using a custom Iselect chip in 6,575 cases and 6,392 controls of European ancestry. Results from the primary scan after imputation were then meta-analyzed with the Iselect results as well as results from previous GWAS. In a combined meta-analysis of the primary scan together with the custom Iselect replication and a previous GWAS, thirteen loci reached genome-wide significance (P < 5 x 10-8) for prostate cancer overall; however, each of them confirmed a previously reported locus. Although they did not reach genome-wide significance, we found evidence for two new suggestive loci at chromosome 16q22.2 (PKD1L3, rs12597458, P = 9.67 x 10-8) and 6p22.3 (CDKAL1, rs12198220, P = 2.13 x 10-7). In a combined case-only analysis of 12,518 prostate cancer cases, we identified two loci associated with Gleason score, a pathological measure of disease aggressiveness: rs35148638 at 5q14.3 (RASA1, P=6.49x10-9) and rs78943174 at 3q26.31 (NAALADL2, P=4.18x10-8). In a stratified case-control analysis, the SNP at 5q14.3 appears specific for aggressive prostate cancer (P=8.85x10-5) with no association for non-aggressive prostate cancer compared to controls (P=0.57). Only the cases and controls genotyped on the HumanOmni2.5 specifically for this study are included under this accession number. Controls (n=101) genotyped with the HumanOmni2.5 for another study are posted under a different accession number. Please note that the majority of prostate cancer cases and controls genotyped in CGEMS (and posted under a different accession number) are included in this study.

  Study phs000882

• Evolutionary histories of breast cancer and related clones

  Study EGAS00001006282

• Identification of novel colorectal cancer predisposition genes

  Study EGAS00001005118

• Multi-Region WES of Metastatic Colorectal Cancer

  Study EGAS00001003573

• Genetic Risk for Subsequent Neoplasms among Long-term Survivors of Childhood Cancer in the St. Jude Lifetime Cohort

  While childhood cancer survivors are known to be at increased risk of subsequent neoplasms (SNs), the contribution of germline mutations in cancer predisposition genes to the risk of SN is largely unknown. Whole-genome sequencing (30X) was performed on 3,006 5+ year survivors of childhood cancer (median age, 35.8 [range: 7.1-69.8] years) from the St. Jude Lifetime Cohort. Survivors underwent a comprehensive clinical assessment. Germline mutations in 156 cancer predisposition genes (SJCPG156), including a subset of 60 (SJCPG60) autosomal dominant genes with moderate to high penetrance, were classified for their pathogenicity. Piecewise exponential regression, stratified by radiation exposure, was used to evaluate the relative rate (RR) and 95% confidence interval (95% CI) of SN occurrence by mutation status. Pathogenic or likely pathogenic mutations in SJCPG156 and SJCPG60 were identified in 11.7% and 5.8% of survivors, respectively. The most frequently mutated SJCPG60 genes included RB1 (n=43), NF1 (n=22), BRCA2 (n=14), BRCA1 (n=12) and TP53 (n=10). Mutations in SJCPG60 were associated with the rate of subsequent sarcoma (RR, 10.3; 95% CI, 4.2 to 25.6) and breast cancer (RR, 13.3; 95% CI, 5.8 to 30.5) among irradiated survivors, and the rate of developing any SN (RR, 4.8; 95% CI, 2.4 to 9.4) and breast cancer (RR, 7.8; 95% CI, 2.5 to 24.0) among non-irradiated survivors. The rate of developing ≥2 histologically distinct SNs was increased 17.8-fold (95% CI, 3.5 to 89.8) among SJCPG60 mutation carriers treated without radiotherapy. Similar but attenuated associations were observed for mutations in SJCPG156. Survivors who develop a SN without prior radiotherapy or who are diagnosed with a subsequent sarcoma or breast cancer within a site of prior radiotherapy should be referred to genetic counseling.

  Study EGAS00001002499

• Breast cancer women lack normal lifelong immune response after full-term pregnancies

  Immunological tolerance during pregnancy is necessary for women’s bodies to accept the semi-allogenic fetus. Interestingly, “immune evasion”, which consists of some similar immunological changes, was recently proposed as a hallmark of cancer. Looking at these results, it seems paradoxical that increasing number of full-term pregnancies (FTP) reduces the risk of breast cancer in women. Our aim was to use a systems epidemiology approach to investigate this paradox by modelling breast cancer incidence as a function of parity in the Norwegian Women and Cancer (NOWAC) cohort, then testing the mathematical model using gene expression from blood in a subcohort of these women: the NOWAC postgenome cohort. Lastly, we undertook a gene set enrichment analysis for immunological gene sets. A linear trend nicely fitted the dataset showing an 8% decrease in risk for each FTP, independent of stratification on other risk factors and lasting for decades after a woman’s last FTP. However, when we looked at gene expression we found that hundreds of genes showed linear trends in cancer-free controls, but this was not the case in /any/ of the samples from breast cancer cases. In the gene set enrichment analysis, samples consisted of human blood or cord blood and mouse bone marrow or spleen. We found more adaptive gene sets than expected in humans and more innate gene sets than expected in mice. None of the gene sets provided information about the long-term effects of immunological tolerance during pregnancy, but the lack of relevant reductionist experiments hampers our interpretation. We suggest that, after resolution at birth, the immunological tolerance induced by pregnancy augments immune response to cancer development.

  Study EGAS00001002616

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Gastric_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003151

• Genome-wide cell-free DNA fragmentation in patients with cancer

  Cell-free DNA (cfDNA) in the blood provides a noninvasive diagnostic avenue for patients with cancer. However, characteristics of the origins and molecular features of cfDNA are poorly understood. We developed an approach to evaluate fragmentation patterns of cfDNA across the genome and found that cfDNA profiles of healthy individuals reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation profiles. We applied this method to analyze fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancers and 245 healthy individuals. A machine learning model incorporating genome-wide fragmentation features had sensitivities of detection ranging from 57% to >99% among the seven cancer types at 98% specificity, with an overall AUC of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation based cfDNA analyses detected 91% of cancer patients. The results of these analyses highlight important properties of cfDNA and provide a proof of principle approach for screening, early detection, and monitoring of human cancer.

  Study EGAS00001003611

• Linked Read Sequencing of Gastric Cancer Metastases for Complex SV Resolution

  In this study, linked read sequencing was performed on two ovarian metastases and matched normal tissue, from a patient with primary diffuse gastric cancer. Linked read sequencing is a DNA preparation technology whereby high molecular weight molecules of DNA are uniquely barcoded prior to fragmentation and sequencing, thus retaining information about genomic contiguity. This study performed an extended analysis of linked read sequencing data to resolve the complex structures of structural variants in the cancer genomes. Complex structural rearrangements were identified in the genomic region surrounding the known oncogene FGFR2, and the association between FGFR2 and gastric cancer metastasis was demonstrated in an organoid model.

  Study phs001362

• CLL_cancer_Sample_Sequencing

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from CLL cancer samples and subjected to total of eight lanes of 37 bp, paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000011

• Glioma_cell_lines_rearrangement_screen

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from commomon epithelial cancer samples and subjected to total of eight lanes of 37 bp, paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000202

• Renal_Follow_Up_Series

  This study's purpose is to use data generated in Renal whole genome and exome Cancer sequencing to target specific areas in multiple other Renal Cancer samples. These areas will then be subjected to bespoke pull downs, tagged and then pool the resultant amplicons. These amplicons will then be sequenced. This is hoped to show the prevalence of previous findings in multiple individuals in a high throughput method.

  Study EGAS00001000095

• Non_Tumour_Renal_Cell_Line_Sequencing

  Genomic libraries (500 bps) will be generated from total genomic DNA derived from commomon epithelial cancer samples and subjected to total of eight lanes of 37 bp, paired end sequencing on the llumina GA. Paired reads will be mapped to build 37 of the human reference genome to facilitate the generation of genome wide copy number information, and the identification of novel rearranged cancer genes and gene fusions.

  Study EGAS00001000205

• Exome sequencing of paired primary tumor and metastatic breast cancer

  Prognosis evaluation of advanced breast cancer and therapeutic strategy are mostly based on clinical features of advanced disease and molecular profiling of the primary tumor. Very few studies have evaluated the impact of a prospective documentation of metastatic subtyping. The genomic landscape of metastatic breast cancer has mostly been described in very advanced, pretreated disease, limiting its transferability to clinical use.

  Study EGAS00001004578

• ANGIOPREDICT - an FP7-funded project enabling personalised medicine for patients with metastatic colorectal cancer.

  In ANGIOPREDICT, academic cancer biologists and industry-based biotechnology researchers will work together with clinicians to identify biomarkers to predict whether individual metastatic colorectal cancer patients will respond positively to Avastin® combination therapy. Diagnostic tests using these biomarkers will also be developed to provide clinicians with the means to predict patient treatment responses in the future.

  Study EGAS00001005423

• Analysis of Loose Ends in Cancer Genome Structure

  Short-read sequencing (SRS) forms the basis of our understanding of cancer genome evolution, yet it is widely thought to be inadequate for detecting structural variants (SVs). To understand the nature of cancer SVs missed by SRS, we introduce the concept of "loose ends" - sites of missing rearrangements revealed by balancing copy number (CN) across the genomic intervals and adjacencies of a genome graph.

  Study EGAS00001007324

• B Cell Receptor Study From Metastatic Breast Cancer Tumour Samples

  B and T cells are key components of the adaptive immune system and play an important role in anti-cancer immunity. In this study, we performed an integrative analysis of the B cell and T cell repertoires across 27 metastatic breast tumours obtained from 8 donors with therapy-resistant lethal metastatic breast cancer at the time of a warm autopsy.

  Study EGAS00001006976

• ESGI-Exome sequencing in Circulating Tumor Cells to determine therapy related markers

  The objectives of this project are the identification of markers related to cancer therapy resistance in the blood of breast cancer patients and to study the genetic changes in cancer cells during this development of resistance. Whole genome amplified DNA from Circulating Tumor Cells (CTCs), selected during the course of systemic treatment from blood of metastatic breast cancer patients, will be exome sequenced . The patients selected for this study did not respond to therapy.

  Dataset EGAD00001001425

• Cancer gene panel (T200.1) sequencing analysis of adult type ovarian granulosa cell tumors (Validation cohort from Hillman, et al)

  Cancer gene panel (T200.1) sequencing data from tumor/normal pairs for adult type ovarian granulosa cell tumor sequencing project. This data set contains 55 tumor panel sequencing data and 44 matched normal panel sequencing data generated using the MD Anderson Cancer Center T200.1 cancer gene hybrid capture platform, with sequencing performed on an Illumina HiSeq 2000. This dataset contains BAM files generated by aligning paired-end reads to the hg19 reference genome.

  Dataset EGAD00001004091

• Molecular portraits of breast cancer diagnosed during pregnancy

  The aim of this study was to compare the mutational landscape of breast cancer diagnosed during pregnancy (BCP) and breast cancer from age/stage non-pregnant patients (controls). We present whole genome sequencing data (Illumina HiSeq X ten platform) of tumor and matched normal tissues from 35 BCP patients and 20 controls. This work provides important novel biological insights and a unique resource to study the biology of breast cancer in young women and how pregnancy could modulate tumor biology.

  Dataset EGAD00001004353

• Osteosarcoma_RNAseq

  We propose to definitively characterise the somatic genetics of Osteosarcoma cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome and transcriptome sequencing.

  Study EGAS00001000615

• GEL_WGS_Comparison

  These samples are to be analysed with the CGP Developed cancer panel and the results will be compared with WGS data from 4 different comercial providers.

  Study EGAS00001000649

• Lung_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Lung cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Study EGAS00001000148

• HKU Gastric Cancer Genomics study - WGS, DNA genotyping array, expression and methylation profiling

  HKU Gastric Cancer Genomics study - Whole Genome Sequencing, DNA genotyping array, Expression profiling and Methylation profiling

  Study EGAS00001000597

• Microdissected Pancreatic Cancer Whole Exome Sequencing

  109 micro-dissected pancreatic cancer cases and normal control tissue were subjected to whole-exome sequencing. Microdissection enriches tumor cellularity and enhances mutation calling.

  Study phs000953

• Mutational Landscape Determines Sensitivity to PD-1 Blockade in Non-Small Cell Lung Cancer

  Patients with non-small cell lung cancer were treated with pembrolizumab. Their tumors and matched normal blood were sequenced.

  Study phs000980

• TOTHER3

  Patritumab deruxtecan in HER2-negative breast cancer: part B results of the window-of-opportunity SOLTI TOT-HER3 trial and biological determinants of early response

  Study EGAS50000000385

• HiSeq Colorectal Cancer Dataset

  Set of 19 patients afflicted with colorectal cancer with matching preoperative and postoperative blood plasma, PBMC, and tumor biopsy sequencing data. Originally referenced by Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring. Nat Med. 2020, Zviran et. al.

  Dataset EGAD00001011186

• Low-coverage whole genome sequencing of plasma from BRCA-mutant breast cancer patients

  Plasma samples from patients with breast cancer (stage IV) who had confirmed BRCA mutations were subjected to low-coverage whole-genome sequencing This dataset contains raw fastq files from 6 breast cancer plasma samples.

  Dataset EGAD50000000810

• Deep whole genome ctDNA chronology of treatment-resistant prostate cancer

  Study EGAS00001005783

• Netherlands Cancer Institute - Breast Cancer Neoadjuvant chemotherapy biomarker studies

  Dac EGAC00001002452

• Cancer Biomarkers team at The ICR DAC

  DAC for Cancer Biomarkers

  Dac EGAC50000000200

• Melbourne Collaborative Cohort Study DNA Methylation Studies

  This dataset contains raw Illumina 450K blood DNA methylation data from a subset of participants in the Melbourne Cohort Study (MCCS), a prospective study of 41,513 healthy adult volunteers (24,469 women) aged between 27 and 76 years when recruited between 1990 and 1994. Nested case-control studies: DNA methylation data were generated as part of cancer case-control studies nested in the MCCS. Participants were cancer-free at blood draw; blood samples were taken at baseline (1990-1994) for 97% of participants; and for 3% of participants at the second wave of follow-up (2003-2007). Eight separate studies were conducted of breast, prostate, colorectal, lung, kidney, urothelial and gastric cancer and B-cell lymphoma, for a total of > 3,500 cancer cases. Controls were individually matched to cases on age, sex, and country of birth using incidence density sampling. Additional matching on smoking history was made for the study of lung cancer. Longitudinal study: For a subset of 1,100 participants with baseline DNA methylation measures (from dried blood spots) who were selected as controls in the nested case-control studies, repeated methylation measures were made using wave 2 follow-up samples (also from dried blood spots) to study longitudinal DNA methylation changes. Project aims: 1. Nested case-control studies: To assess prospective associations between peripheral blood DNA methylation and risk of eight cancer types (breast, prostate, colorectal, lung, kidney, urothelial cell and gastric cancer, and mature B-cell neoplasms). 2. Longitudinal study: To assess associations between lifestyle changes and changes in peripheral blood DNA methylation.

  Study phs003213

• Benchmarking for alignment and variant calling

  Background: Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and six structural variant callers comprised of four generic callers (Sniffles2, cuteSV, SVIM and DELLY in generic mode) and two somatic callers (nanomonsv and DELLY in somatic modes). Results: Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short read sequencing. When compared to somatic structural variants detected with short read sequencing, more events were detected with long read sequencing. The mean recall of somatic variant events identified by short read sequencing was higher for the somatic callers (64%) than generic callers (52%), with nanomonsv (69%) showing the best performance. Conclusion: Long read sequencing can identify somatic structural variants. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

  Study EGAS00001007819

• Integrative pan-cancer genomic and transcriptomic analyses of refractory metastatic cancer

  Study EGAS00001006648

• A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  Study EGAS00001000245

• Activating AKT1 and PIK3CA mutations in metastatic castration-resistant prostate cancer

  Study EGAS00001004328

• Cancer Clinical Research Trust DAC for WES of HER2+ metastatic cancer samples

  Dac EGAC00001001632

• RNAseq

  RNAseq of pancreatic cancer organoids.

  Study EGAS00001007212

• Genome analysis of early onset sporadic rectal cancer

  Study EGAS00001005970

• Molecular analysis in bowel malignancies in cancer survivors vs. primary malignancies

  Study EGAS00001005940

• Single-cell RNA sequencing of bronchoalveolar lavages from COVID-19 patients

  Discriminating mild-moderate from critical COVID-19 disease by innate and adaptive immune single-cell profiling of bronchoalveolar lavages.

  Study EGAS00001004717

• A novel subset of human CD33+ haematopoietic stem cells characterized at single-cell resolution

  This dataset comprises single-cell RNA sequencing of the human Lin-CD34+38-45RA-90+49f+ phenotype isolated from 2 normal cord donors. Library preparation was performed following a modified CEL-Seq2 protocol.

  Dataset EGAD00001003955

• Vγ9Vδ2-T cells in chronic lymphocytic leukemia patients and healthy controls

  RNA sequencing data from Vγ9Vδ2-T cells from chronic lymphocytic leukemia patients and age-mnatched healthy controls. Matched Vγ9Vδ2-T cell samples before and after expansion with autologous monocyte-derived dendritic cells for each donor are included.

  Dataset EGAD00001004325

• Genomic Landscape of Radiation Induced Meningiomas

  EGAS00001002317 - Whole exome sequencing of data of 18 RIMs with matched bloods. Median depth of 112x (range of 110-120). Performed on Illumina HiSeq Platform. EGAS00001002318 - RNA sequencing data of 18 RIMs on the Illumina HiSeq Platform.

  Dataset EGAD00001004358

• Transcriptomic origins of mpMRI visibility

  We profiled the transcriptomes (RNA-sequencing) of 40 clinically significant invisible and visible tumors, all with ISUP Grade 2 disease and treated by radical prostatectomy. Twenty tumors were mpMRI invisible (PI-RADSv2: 1-2), while 20 tumors were visible (PI-RADsv2: 5).

  Dataset EGAD00001004397

• Total RNAseq in the sporadic ALS and healthy control motor cortex

  The motor cortex is the earliest affected brain region in ALS. This dataset contains total RNA sequencing (stranded, 2x101bp) data derived from the motor cortex of 11 sporadic ALS patients and 8 healthy controls.

  Dataset EGAD00001006022

• Potent neutralizing antibodies against SARS-CoV-2

  The COVID-19 pandemic urgently needs therapeutic and prophylactic interventions. Here we report the rapid identification of SARS-CoV-2 neutralizing antibodies by high-throughput single-cell RNA and VDJ sequencing of antigen-enriched B cells from 60 convalescent patients.

  Dataset EGAD00001006130

• MPNST_Data

  WES from 51 cases initially diagnosed as Malignant Nerve Sheath Tumours (MPNST) and RNA sequencing data from 10 MPNST cases. Find more information in article: Lyskjær et al, 2020, J Pathol, "H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours".

  Dataset EGAD00001006253

• Single nucleus and in situ RNA sequencing reveals cell topographies in the human pancreas

  To investigate the cellular composition of the human pancreas, we performed single-nucleus sequencing from snap frozen biopsies of pancreata from adult, neonatal and diseased (chronic pancreatitis) human donors.

  Dataset EGAD00001006396

• Inherited CD28 deficiency in otherwise healthy patients with disseminated warts and giant horns

  this dataset corresponds to 3 patient of HPV-driven warts single cell RNA data generated through the 10X genomics platform and aligned on GRCh38 reference using the cell ranger tools.

  Dataset EGAD00001006644

• ACC RNASeq data

  Samples prepared using TruSeq Stranded Total RNA library kit. Samples sequenced on a HiSeq 2000.

  Dataset EGAD00001008192

• Sequencing data for oesophageal and related samples - Ng, Contino et al (RNA)

  Data supporting: "Interplay of processes shapes structural variations undergoing selection in oesophageal adenocarcinoma" Ng, Contino et al. RNAseq (BAM files) 214 oesophageal adenocarcinoma samples

  Dataset EGAD00001007809

• Sequencing data for oesophageal and related samples - Alex Frankell et al (RNA)

  Data supporting: "The landscape of selection in 551 Esophageal Adenocarcinomas defines genomic biomarkers for the clinic." Frankell et al. RNAseq (BAM files) 116 tumours

  Dataset EGAD00001004423

• RNAseq of SCCOHT patient tumors

  This data set contains BAM files of the RNAseq analysis for three SCCOHT patient tumors. Total mRNA was isolated from fresh frozen tumor samples. RNA sequencing was performed using Illumina HiSeq 4000, paired end 150 bp.

  Dataset EGAD00001007829

• Single cell study of infant leukemias

  We have performed single cell RNA-sequencing for infant and childhood B-cell acute lymphoblastic leukemias as well as infant acute myeloid leukemias at diagnosis. The sequencing was performed with 10X Chromium single cell 3’ and 5’ chemistry.

  Dataset EGAD00001007853

• RNAseq of preneoplasia lung adenocarcinoma

  RNA sequencing of 168 pulmonary samples including lung preneoplasia atypical adenomatous hyperplasia (AAH, N=38), adenocarcinoma in situ (AIS, N=22), minimally invasive adenocarcinoma (MIA, N=19) and invasive lung adenocarcinoma (ADC, N=38) and adjacent lung tissues (Normal, N=62).

  Dataset EGAD50000000395

• Single-cell RNA sequencing data of patients with T follicular helper cell lymphomas

  This dataset contains single-cell count data generated by the Cellranger pipeline (v3.1.0, 10X Genomics) from 9 LN and 16 PB samples of 14 patients with T follicular helper cell lymphomas (TFHLs) as well as 7 homeostatic LN (HLN) samples.

  Dataset EGAD50000000402

• Pregnancy-associated melanoma

  The aim of this project is to assess differences in intratumoral immune composition in pregnant melanoma patients versus non pregnant melanoma controls. Samples (N=25) were obtained from a local patient database. From archived FFPE we isolated RNA and performed NGS and bio-informatica data-analysis.

  Dataset EGAD50000000706

• RNAseq of samples from CLL patients treated with ibrutinib in vivo

  The dataset contains RNA sequencing data from 22 paired samples of 11 patients before and during ibrutinib therapy (median time on therapy 2 weeks; range 1-12 weeks). The sequencing was performed in two batches.

  Dataset EGAD50000000879

• AACR Project Genomics, Evidence, Neoplasia, Information, Exchange (GENIE)

  AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pancancer registry of real-world data assembled through data sharing between 19 leading international cancer centers with the goal of improving clinical decision-making. The registry leverages ongoing clinical sequencing efforts (CLIA/ISO-certified) at participating cancer centers by pooling their data to create a novel, open-access registry to serve as an evidence base for the entire cancer community. Genomic and baseline clinical data from more than 70,000 tumors is accessible through the efforts of our strategic and technical partners, Sage Bionetworks and cBioPortal. The consortium and its activities are driven by openness, transparency, and inclusion to ensure that the project output remains accessible to the global cancer research community and ultimately benefits patients.

  Study phs001337

• Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.

  Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dac EGAC50000000169

• Geriatric Oncology Database of genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients to establish truly effective treatment strategy

  Owing to the advent of super-aged society, cancer mortality in Japan is forecasted to become an all-time high. The management of elderly patients with cancer is a serious health issue and the need for specific care guidelines for this population is critical in Japan. The significant individual differences in comorbidity, physical and mental functioning, and social problems among aging individuals are obstacles to the progress. The response to cancer treatment varies significantly among patients, even in the same stage of the same type of cancer. Older aged patients are still less likely to be offered participation in clinical trials, thus the number of clinical evidences is limited. The molecular mechanisms regulating the physiological process of ageing and senescence, and cancer are far from understood. To establish a truly effective treatment algorithm, we attempted to develop a geriatric oncology database for genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients in this retrospective study. The genomic analysis was performed in 62, 106, and 173 cases, respectively for gastric, colon and lung cancers. The clinical data and survey results on psychosocial and physical conditions were collected from 166, 313, and 344 patients respectively for gastric, colon and lung cancers, and also collected from 357, 49, and 300 benign cases respectively for cardiovascular disorder, respiratory dysfunction, diabetes and nephropathy as the analysis control.

  Study JGAS000061

• Use of Whole Genome Sequencing for Diagnosis and Discovery in the Cancer Genetics Clinic

  Despite the potential of whole-genome sequencing (WGS) to improve patient diagnosis and care, the empirical value of WGS in the cancer genetics clinic is unknown. We performed WGS on members of two cohorts of cancer genetics patients: those with BRCA1/2 mutations (n = 176) and those without (n = 82). Initial analysis of potentially pathogenic variants (PPVs, defined as nonsynonymous variants with allele frequency < 1% in ESP6500) in 163 clinically-relevant genes suggested that WGS will provide useful clinical results. This is despite the fact that a majority of PPVs were novel missense variants likely to be classified as variants of unknown significance (VUS). Furthermore, previously reported pathogenic missense variants did not always associate with their predicted diseases in our patients. This suggests that the clinical use of WGS will require large-scale efforts to consolidate WGS and patient data to improve accuracy of interpretation of rare variants. While loss-of-function (LoF) variants represented only a small fraction of PPVs, WGS identified additional cancer risk LoF PPVs in patients with known BRCA1/2 mutations and led to cancer risk diagnoses in 21% of non-BRCA cancer genetics patients after expanding our analysis to 3209 ClinVar genes. These data illustrate how WGS can be used to improve our ability to discover patients' cancer genetic risks. "Reprinted from doi:10.1016/j.ebiom.2014.12.003, with permission from EBioMedicine."

  Study phs000942

• Genomic profiling of patient-derived xenografts and organoids in prostate cancer

  Study EGAS00001004673

• Molecular Profiles of BRCA1-Associated Ovarian Cancer Treated by Platinum-Based Therapy

  Study EGAS00001003980

• Genotyping by array

  Expression profiling by Nanostring cancer pathway

  Dataset EGAD00010001276

• Cancer Alliance Exome

  Exome sequencing for individualized cancer interpretation

  Dataset EGAD00001006236

• Prostate Cancer mitochondrial DNA heteroplasmies and mitochondrial gene expression

  Study EGAS00001004186

• Genomics_of_acral_lentiginous_melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003740

• Genomic analysis of HPV positive versus HPV negative esophageal adenocarcinoma

  High-risk human papillomavirus (hr-HPV) has been implicated in a subset of patients with esophageal adenocarcinoma (EAC). We therefore hypothesized that HPV associated EAC may have distinct genomic aberrations compared with viral negative esophageal cancer as shown in Head and Neck cancer and cervical cancer. Whole exome sequencing (WES) was performed to explore the mutational landscape and potential molecular signature of HPV positive versus HPV negative EAC, which includes four hr-HPV-positive and 8 HPV-negative treatment naive fresh-frozen EAC tissue specimens and matched normal tissues.

  Study EGAS00001001340

• Targeted sequencing of breast cancers with germline BRCA1/2 mutations

  Breast cancer is the most prevalent cancer in women, where a germline predisposition plays a substantial role. However, the effects of pathogenic germline variants on accompanying breast cancers have not been fully characterized in terms of somatic alterations. We obtained tumor samples from 30 patients with pathogenic germline variants in BRCA2 (n = 25) and BRCA1 (n = 5), as well as an additional 30 patients without pathogenic germline mutations, in which somatic mutations in common breast cancer drivers and CNAs were analyzed using targeted panel sequencing.

  Study EGAS00001004182

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Cancer cells enter a reversible drug tolerant persister (DTP) state to evade death from both chemotherapies and targeted agents. It is increasingly appreciated that the DTP state is an important driver of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer xenograft models to identify and characterize the cancer cells capable of generating DTPs in response to standard-of-care chemotherapy. Barcode analysis revealed no loss in clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fits a mathematical model in which all cancer cells, and not a small subpopulation, possess an equipotent capacity to enter the DTP state. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides new insights into how cancer cells use a developmentally conserved mechanism to drive the DTP state pointing to novel therapeutic opportunities to target diapause-like DTPs.

  Dataset EGAD00001006849

• Cancer Single Cell Sequencing

  This study is to ascertain whether it is feasible to extract a single cell form a Cancer cell line, amplify it and sequence it.

  Study EGAS00001000003